NDLI: Nominally robust model predictive control with state constraints

Content Provider	IEEE Xplore Digital Library
Author	Grimm, G. Messina, M.J. Tuna, S.E. Teel, A.R.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA (Grimm, G.; Messina, M.J.; Tuna, S.E.; Teel, A.R.)
Abstract	We present robust stabilization results for constrained, discrete-time, nonlinear systems using a finite-horizon model predictive control (MPC) algorithm that does not require any particular properties for the terminal cost. We introduce a property that characterizes the robustness properties of the MPC optimization problem. Assuming the system has this property (for which we give sufficient conditions), we make two further key assumptions. These are that the value function is bounded by a K/sub /spl infin// function of a state measure (related to the distance of the state to some target set) and that this measure is detectable from the stage cost used in the MPC algorithm. We show that these assumptions lead to stability that is robust to sufficiently small disturbances and measurement noise. While in general the results are semiglobal practical, when the detectability and upper bound assumptions are satisfied with linear K/sub /spl infin// functions, the stability and robustness is global with respect to the feasible set. We discuss algorithms employing terminal equality or inequality constraints. We provide two examples, one involving a terminal equality constraint and the other involving a nonrobustness-inducing state constraint.
Sponsorship	Honeywell Lab. Xerox Nat. Instruments Math Works
Starting Page	1413
Ending Page	1418
File Size	447989
Page Count	6
File Format	PDF
ISBN	0780379241
ISSN	01912216
DOI	10.1109/CDC.2003.1272808
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robust control Predictive models Predictive control Robust stability Noise robustness Nonlinear systems Prediction algorithms Sufficient conditions Cost function Noise measurement
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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